Dental Students’ Ability to Detect and Diagnose Oral Mucosal Lesions

Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification

Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias. The model integrates three components: (i) a Classification Stream, utilizing a CNN to categorize images into 16 lesion types (baseline model), (ii) a Guidance Stream, which aligns class activation maps with clinically relevant areas using ground truth segmentation masks (GAIN model), and (iii) an Anatomical Site Prediction Stream, improving interpretability by predicting lesion location (GAIN+ASP model). The development dataset comprised 2765 intra-oral digital images of 16 lesion types from 1079 patients seen at an oral pathology clinic between 1999 and 2021. The GAIN model demonstrated a 7.2% relative improvement in accuracy over the baseline for 16-class classification, with superior class-specific balanced accuracy and AUC scores. Additionally, the GAIN model enhanced lesion localization and improved the alignment between attention maps and ground truth. The proposed models also exhibited greater robustness against dataset bias, as shown in ablation studies.

Dental Antimicrobial Stewardship: Developing a Mobile Application for Rational Antibiotic Prescribing to Tackle Misdiagnosis

BACKGROUND/OBJECTIVES

Inexperienced dentists and dental students are especially prone to misdiagnosis, and this represents a huge problem regarding antimicrobial stewardship. We aimed to develop a mobile app for rational antibiotic prescribing in dentistry based on local-systemic symptoms and patient factors, rather than solely on diagnosis, to tackle misdiagnosis.

METHODS

The study involved 64 participants, 50 of which were third-year dental students attending a pharmacology course focusing on antimicrobials, comprising lectures and practical sessions without (noAPP group, n = 22) or with (APP group n = 28) the assistance of a mobile application. The other 14 participants were practicing dentists who decided to register and use the application. All registered users of the application were asked to take a feedback survey, while learning outcomes were evaluated via a pharmacology quiz.

RESULTS

A decision tree was used for application development. In total, 76 impressions were collected on the application. The majority of the impressions were related to odontogenic-endodontic infections. Multiple linear regression analysis did not reveal differences in survey responses between practicing dentists and undergraduate students in the feedback survey responses. There was a significant difference in the mean pharmacology test scores between the noAPP and APP groups (5.50 ± 1.80 vs. 7.21 ± 1.03, p = 0.0001).

CONCLUSIONS

The dentalantibiotic.com application was developed to support rational antibiotic prescribing, in view of tackling misdiagnosis, among inexperienced dentists, as well as to assist in undergraduates' pharmacology learning, and the current study shows its large impact as an educational tool. The majority of participants considered it easy to use, efficient in facilitating the right antibiotic choice, and useful for everyday decision-making.

Factors important in the correct evaluation of oral high-risk lesions during the telehealth era

BACKGROUND

Considering that early detection of squamous cell carcinoma (SCC) improves prognosis and clinical examination is the primary detection method, we identified factors related to the clinical evaluation of oral mucosal lesions. Due to the growing role of telehealth, our study was based on clinical image evaluation.

SUBJECTS AND METHODS

Oral medicine specialists and dental students evaluated six images of benign, potentially malignant, or SCC lesions (18 images in total). We analyzed the role of personal factors of the examiners and the visual pathological features of the lesion upon which the participants based their evaluation.

RESULTS

One hundred thirty-three subjects participated. Half of the benign images were correctly evaluated. On average 1.2 (±SD1.3) cancer pictures were recognized correctly and 3.66 (±SD1.42) images were considered potentially malignant. Potentially malignant lesions were correctly evaluated at an average of 4.08 (±SD1.48) images. For cancer and potentially malignant lesion images, there were significantly better results among clinicians with the worst results from the fourth-year students. Student results correlated significantly with years of study, number of weeks spent in the oral medicine clinic, and interest in oral pathology. Consideration of lesion irregularity yielded a correct diagnosis, whereas wrong answers were based on color changes. Lesion size and margins were considered equally important.

CONCLUSIONS

Using clinical images as part of the diagnostic process provides good results, though increased clinical experience for graduates and undergraduates may be necessary to improve accuracy. Therefore, emphasizing the important visual parameters of malignancy may be valuable in the current telehealth era.

Perception and Attitude of Dental Students and Interns Regarding the Diagnosis and Management of Oral Mucosal Lesions and Salivary Glands Hypofunction

Background:

The perception and attitude of dental students/graduates regarding diagnosing/managing oral medicine cases are scarcely investigated.

Objective:

The aim of this investigation was to evaluate the level of confidence in diagnosing/managing cases of oral mucosal lesions and salivary glands hypofunction.

Methods:

A 29-items questionnaire descriptive survey was distributed among dental interns and sixth-year students in the city of Jeddah during March-April of 2020.

Results:

A total of 136 (81 interns and 55 sixth-year students) completed the questionnaire, of which 69.9% were from a government school, and 30.1% were from private schools. For oral mucosal lesions [i.e., aphthous/herpes simplex virus ulceration], the majority of government and private schools’ participants reported being confident in their ability to diagnose (88.4% and 87.8%, respectively) and provide treatment (63.2% and 56.1%, respectively). For oral candidiasis, the majority were confident in their ability to diagnose (government: 95.8%; private: 59.1%) and treat (government: 77.9%; private: 65.9%). The confidence in diagnosing lesions suspicious for dysplasia/premalignancy was high in 77.9% of government and 80.5% of private schools. Similar reporting was found regarding salivary hypofunctions (government: 93.7%; private: 90.2%). For the likeness to refer, the majority of participants were likely to refer to oral medicine, as the 1st choice, followed by oral surgery.

Conclusion:

Dental interns/sixth-year students seemed to have high levels of confidence in diagnosing/managing oral mucosal lesions and salivary hypofunctions. However, the partial participation and the subjectivity of reporting may have hindered capturing the full/precise picture.

Evaluation of the quality of referral letters: experience of a Brazilian oral medicine service

Optimizing the quality of referral letters could be the first step to a correct clinical approach for patients. Referral letters should be legible and contain the necessary information to avoid delaying the patient's diagnosis and treatment. However, to date, few studies have been conducted on how referrals are performed in Brazil. Knowledge regarding the quality of referral letters can provide information to better guide health care professionals. This study was aimed at analyzing all referrals received by a single oral medicine service in Brazil. Referral letters were classified into poor, regular, good, and excellent based on key items concerning the primary morphology of the lesion, location, diagnostic hypothesis, symptomatology, time of evolution, consistency, size, and limits. A total of 500 referral letters were evaluated, including 271 (54.2%) from a private service and 229 (45.8%) from a public service. Dentists and physicians had written 475 (95%) and 25 (5%) referral letters, respectively. Among the 500 referrals analyzed in this study, the number of regular, poor, good, and excellent referrals was 236 (47.2%), 203 (40.6%), 58 (11.6%), and one (0.6%), respectively, showing a lack of important clinical information in referrals.